The linear Gaussian state space model for which the common variance is treated as a stochastic time-varying variable is considered for the modelling of economic time series. The focus of this paper is on the simultaneous estimation of parameters related to the stochastic processes of the mean...

We investigate changes in the time series characteristics of postwar U.S. inflation. In a model-based analysis the conditional mean of inflation is specified by a long memory autoregressive fractionally integrated moving average process and the conditional variance is modelled by a stochastic...

The paper studies the effects of cross-country differences in the production process of human capital on income distribution and growth. Our overlapping gen- erations economy has the following features: (1) consumers are heterogenous with respect to parental human capital and wealth; (2)...

The paper examines the effect of heterogeneity in individual human capital formation on cross-country income inequality. It considers a two-country model of overlapping generation heterogeneous economies with the following features: (1) individuals are heterogeneous with respect to inborn...

This paper presents results of a meta-regression analysis on empirical estimates of capital-energy substitution. Theoretically it is clear that a distinction should be made between Morishima substitution elasticities and cross-price elasticities. The former represent purely technical...

Policy in developed countries is often based on the assumption that higher business ownership rates induce economic value. Recent microeconomic empirical evidence casts doubts on the validity of this assumption or, at least, leads to a more nuanced view: Especially the top performing business...

Many seasonal macroeconomic time series are subject to changes in their means and variances over a long time horizon. In this paper we propose a general treatment for the modelling of time-varying features in economic time series. We show that time series models with mean and variance functions...

We propose a new class of observation driven time series models referred to as Generalized Autoregressive Score (GAS) models. The driving mechanism of the GAS model is the scaled score of the likelihood function. This approach provides a unified and consistent framework for introducing...

This discussion paper has resulted in a publication in the A rated journal 'Journal of Business and Economic Statistics'.<p>